In a previous paper [1]}, we introduce a novel distributional representation for CGM data, termed glucodensity, which allows us to obtain a functional profile of patient glucose homeostasis. Glucodensity is a natural extension of Time in Range (TIR) metrics, that measures the proportion of time a person spends with their blood glucose levels within the target range of \(70-180\)  mg/dL [2]}, [3]}. Although very intuitive, TIR metrics have two main disadvantages: first, the range fits poorly depending on the characteristics of the population examined; second, there is a loss of information caused by the discretization of the recorded data into intervals. Instead, glucodensity effectively measures the proportion of time each individual spends at a specific glucose concentration. Previous results for glucodensities show a better predictive performance as compared to common diabetes biomarkers.
